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AdvisorErrad, Abdelkarim
AdvisorElsayed, Tamer
AuthorSalim, Nazar S.
Available date2019-03-11T11:35:51Z
Publication Date2018-06
URIhttp://hdl.handle.net/10576/11401
AbstractWith the emergence of the massive volume of content through social media platforms, users are getting overwhelmed with information, though searching for the topic will give you filtered information that interests you. Yet, if the user is subscribed to multiple topics one of them might shadow that topic of interest. The project was created to address this issue through offering a mobile application for users to define their topics of interest. The application named Real-time Twitter Summarization (RTS) offers a novel approach where user gets to not only choose the topic, but to decide on frequency and relevancy of the pushed tweets related to the topic. The application also provides a real time summarization, and offers notification once topic related novel tweet was created. These functionalities are solutions that were not provided in similar applications. This project has not only been developed to be fully functional, but to also be usable in the simplest format. Scalability of the tweet summarization Engine was tested , to check if the application layer did cause delay or not. It is important to mention that this work is an extension to the previous work of Suwaileh, Reem and Hasanain, Maram [7] submitted as a participation of “Real-Time Summarization Track” [3].
Languageen
SubjectMobile Application
SubjectReal-Time Summarization
SubjectScalability
SubjectRTS
SubjectInformation Retrieval
SubjectInformation Filtering
TitleReal-time Tweet Summarization Mobile Application
TypeProfessional Masters Project
DepartmentComputing


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